Workshop
on
Dynamic
Data-Driven Applications Systems (DDDAS)
Location:
NSF, Arlington(Ballston), VA
The
objectives of the workshop are:
1)
Provide a forum for current and other potential stakeholders of
DDDAS technologies,
2)
Engage communities which have applications of great national and
technical importance that can benefit from the DDDAS concept, and
3)
Provide a forum for discussion of: the enhancements enabled by
DDDAS, assessments of state-of-the-art technological capabilities to support
DDDAS environments, and, the research challenges, innovations and technology
advances needed to support DDDAS environments.
The workshop discussions will be summarized in a report, which will be made available to the broader community.
There
will be four Working Group (WG) tracks:
WG1 – Applications; Co-Chairs: Seidel and Chaturvedi
WG2 – Mathematical & Statistical
Algorithms; Co-Chairs:
Douglas and Biros
WG3 – Measurements: Co-Chairs: Baldridge and How
WG4 – Systems Software: Co-Chairs: Parashar and Sussman
Below
is a brief list of possible items to be addressed by each working group.
The discussions will be driven by topics deemed suitable by the WG attendees
and led by the WG co-Chairs.
Together with WG breakouts there will be two joint sessions (an interim
and a closing one), where the groups will be brought together to discuss items
of joint interest. After the
sessions, WG co-Chairs will finalize the Workshop Report which will be posted
on the DDDAS webpage (www.cise.nsf..gov/dddas)
Some
of the items to be discussed (but not limited to) include:
WG1
– Applications (possibly
W1a & W1b - TBD)
What
are the opportunities and challenges in enabling DDDAS capabilities? What research and technologies are covered
by the present projects? Provide
applications examples that will benefit from the new paradigm, existing
and potential new applications, challenges in developing such applications,
multilevel and multimodal modeling, composition of such complex applications,
data management and interfaces to experiments/field-data, computation, memory
and I/O requirements. As these
requirements are expected to be dynamic, what are the implied applications
modeling technology advances that are need and whatÕs the needed systems
support? What are the issues
in data management, dynamic selection of application components, mapping,
interfaces for request and allocation of systems resources so that quality of
service is ensured for the applications?
What
is the state-of-the-art and what are the challenges in the applications
algorithms to enable such capabilities ?
What advances are needed to enable application algorithms that are
tolerant to perturbations from Òon-lineÓ input data and have stability properties? How can
one select and incorporate dynamically appropriate algorithms as the
application requirements and data sets change in the course of simulation? What
kinds of approaches, such as knowledge-based systems, can be employed, and what
interfaces and applications assists are needed to enable such
capabilities? What systems support
is required to develop such environments?
What
is the state of the art in measurement systems and how are they integrated in
DDDAS? For example, where
measurements from sensors, other instruments and data repositories are
dynamically integrated with the application modeling to improve the application
modeling, and, the converse, where the on-line application control of the
measurement instrument or process provides opportunity to improve the
measurement process, guide the design and operational aspects of measurement
instruments, guide the architecture of sets of sensors and other instruments
thus improving the effectiveness or efficiency of the measuring systems. What are the challenges and
opportunities in software and hardware technologies to enable such dynamic
interfaces? What improvements in the measurement methods are expected? How are
they going to be enabled?
What
is the state-of-the-art and what advances are needed in computer systems
software methods and tools, and what new capabilities should be provided by the
underlying systems and platforms on which these applications execute, so
that quality of service is ensured? What are the software challenges in the
programming environments for the development and runtime support, under
conditions where the underlying resources as well as the applications
requirements might be changing at execution time? What are the challenges to integrate real-time sensor and
other measurement devices with special purpose data processing systems together
with the parts of the application that execute in larger platforms and drive a
seamless integration of stationary and mobile devices together with large
high-end platforms, entailing grids that go beyond the present computational
grids? What are the issues with respect to data management, data models and
structures, and interfaces between simulations and measurements? What are the additional capabilities
that are needed in the application support and systems management services?
In
addition all the WGs are expected to address the following issues: why is now
the right time for fostering this kind of research? What venues and mechanisms are optimal to facilitate the
multidisciplinary nature of the research needed in enabling such
capabilities? What existing or
planned initiatives exist that support such efforts? How can these new research directions be used to create some
exciting opportunities for student education and training? What new opportunities are created for
postdoctoral experiences? What kinds
of connections among academic, industrial and federal sectors, as well as
interactions with the international community, can be beneficial? How can these be fostered
effectively to focus research efforts and expedite technology transfer? How does DDDAS enable new applications
and impacts other new research directions and advances? What are the grand
challenges whose solutions maybe enabled by DDDAS?